def _load(self) -> None:
"""
Load file from Meteostat
"""
# File name
file = 'stations/slim.csv.gz'
# Get local file path
path = get_file_path(self.cache_dir, self.cache_subdir, file)
# Check if file in cache
if self.max_age > 0 and file_in_cache(path, self.max_age):
# Read cached data
df = pd.read_pickle(path)
else:
# Get data from Meteostat
df = load_handler(self.endpoint, file, self._columns, self._types,
self._parse_dates, True)
# Add index
df = df.set_index('id')
# Save as Pickle
if self.max_age > 0:
df.to_pickle(path)
# Set data
self._data = df
def _load(
self,
station: str
) -> None:
"""
Load file from Meteostat
"""
# File name
file = f'normals/{station}.csv.gz'
# Get local file path
path = get_file_path(self.cache_dir, self.cache_subdir, file)
# Check if file in cache
if self.max_age > 0 and file_in_cache(path, self.max_age):
# Read cached data
df = pd.read_pickle(path)
else:
# Get data from Meteostat
df = load_handler(
self.endpoint,
file,
self._columns,
self._types,
None)
if df.index.size > 0:
# Add weather station ID
df['station'] = station
# Set index
df = df.set_index(['station', 'start', 'end', 'month'])
# Save as Pickle
if self.max_age > 0:
df.to_pickle(path)
# Filter time period and append to DataFrame
if df.index.size > 0 and self._end:
# Get time index
end = df.index.get_level_values('end')
# Filter & return
return df.loc[end == self._end]
return df
def _load(
self,
station: str
) -> None:
"""
Load file for a single station from Meteostat
"""
# File name
file = 'daily/' + ('full' if self._model else 'obs') + \
'/' + station + '.csv.gz'
# Get local file path
path = get_file_path(self.cache_dir, self.cache_subdir, file)
# Check if file in cache
if self.max_age > 0 and file_in_cache(path, self.max_age):
# Read cached data
df = pd.read_pickle(path)
else:
# Get data from Meteostat
df = load_handler(
self.endpoint,
file,
self._columns,
self._types,
self._parse_dates)
# Validate Series
df = validate_series(df, station)
# Save as Pickle
if self.max_age > 0:
df.to_pickle(path)
# Filter time period and append to DataFrame
if self._start and self._end:
# Get time index
time = df.index.get_level_values('time')
# Filter & return
return df.loc[(time >= self._start) & (time <= self._end)]
# Return
return df
def _load(self, station: str, year: str = None) -> None:
"""
Load file from Meteostat
"""
# File name
file = 'hourly/' + ('full' if self._model else 'obs') + '/' + \
(year + '/' if year else '') + station + '.csv.gz'
# Get local file path
path = get_file_path(self.cache_dir, self.cache_subdir, file)
# Check if file in cache
if self.max_age > 0 and file_in_cache(path, self.max_age):
# Read cached data
df = pd.read_pickle(path)
else:
# Get data from Meteostat
df = load_handler(self.endpoint, file, self._columns, self._types,
self._parse_dates)
# Validate Series
df = validate_series(df, station)
# Save as Pickle
if self.max_age > 0:
df.to_pickle(path)
# Localize time column
if self._timezone is not None and len(df.index) > 0:
df = df.tz_localize('UTC', level='time').tz_convert(self._timezone,
level='time')
# Filter time period and append to DataFrame
if self._start and self._end:
# Get time index
time = df.index.get_level_values('time')
# Filter & return
return df.loc[(time >= self._start) & (time <= self._end)]
# Return
return df